Supplementary Materials for Trees have overlapping potential niches that extend beyond their realized niches Daniel C. Laughlin and Brian J. McGill Corresponding author: Daniel C. Laughlin, daniel.laughlin@uwyo.edu Science 385, 75 (2024) DOI: 10.1126/science.adm8671 The PDF file includes: Materials and Methods Figs. S1 to S7 Tables S1 and S2 References Materials and Methods We estimated empirical realized and potential niches along global temperature gradients using occurrence data for 188 North American tree species. We submitted a data request to Botanic Gardens Conservation International (BGCI) for lists of arboreta in which 298 North American trees were growing and surviving. We received information from 447 arboreta around the world (Fig. S1) (32). After taxonomic matching, we analyzed the 188 species that had a minimum of 20 occurrences in arboreta and for which natural occurrence data was available (Fig. S1, S2). Realized niches for each species were quantified as the range of climate conditions across their native ranges in North America. We downloaded native occurrence data for these species from the Botanical Information and Ecology Network (BIEN 4.1) (30). We removed cultivated records from the BIEN data to ensure these were native occurrence records and limited all occurrences to within North America. We supplemented occurrence records in BIEN with point samples from Little’s range maps (31) to ensure full sampling of species ranges into Canada and Mexico. We used CHELSA V2.1 climate normals (1980-2010) (33) to quantify mean annual temperature, maximum temperature of the warmest month, and minimum temperature of the coldest month for each occurrence record (Fig. S1). Potential niches for each species were quantified as the range of climate conditions across their native ranges in North America in addition to the range of climate conditions across the globally-distributed arboretums (i.e., native occurrences plus arboreta occurrences), because realized niches are subsets of potential niches (5, 10). We use the term ‘potential niche’ to represent the conditions that permit survival (but with no information about reproduction) (6, 7), which is equivalent to the ‘tolerance niche’ (5), but differs from the paleoecological concept of a ‘potential niche’ defined as the intersection between the fundamental niche and realized environmental space at any given time (26). Given that natural occurrences outnumbered the arboretum occurrences by several orders of magnitude and would overwhelm the estimates of niche ranges, we randomly sampled occurrences from BIEN and Little’s range maps at 10 times the number of occurrences in the arboretums for a total of 165,315 occurrences. Random samples using different starting conditions yielded consistent results (Table S2). Three niche metrics were computed for each of the 188 species to test the three models of niche architecture. These metrics focus on the ranges of temperatures (including mean annual temperature, minimum temperature of the coldest month, and maximum temperature of the warmest month) in which a species could grow and survive. Quantiles were preferred over absolute minimum and maximum values to prevent biasing metrics toward extreme outliers (53). Each metric was calculated using four quantities: the minimum realized niche Rmin (0.01 quantile), the maximum realized niche Rmax (0.99 quantile), the minimum potential niche Pmin (0.01 quantile), and the maximum potential niche Pmax (0.99 quantile). First, niche widths were computed as a range of temperatures, where realized niche width = Rmax – Rmin, and potential niche width = Pmax – Pmin. Second, we computed the ratio of the realized niche width -topotential niche width, where R:P ratio = (Rmax – Rmin ) / (Pmax – Pmin) (Fig. 1). Third, we computed an index of niche contraction (Fig. 1), where niche contraction = [(Rmin – Pmin) – (Pmax – Rmax )] / (Pmax – Pmin). Positive values of niche contraction indicate contraction of the realized niche into warmer climates and negative values indicate contraction into cooler climates. We regressed each of the three metrics on realized niche positions (medians, 0.5 quantile). We tested for linear and quadratic polynomial relationships and report the model most supported by data assessed using likelihood ratio tests and AIC (Table S1). The number of occurrences in arboreta for each species ranged from 20 to 268, with a median of 78 occurrences per species (Fig. S2). We tested whether the number of occurrences in arboreta for each species could affect the likelihood of detecting a contraction of the potential niche, by regressing each of the niche metrics on the number of occurrences. The R:P ratio exhibited a positive yet weak (R2 = 0.05) relationship with number of occurrences, but this positive relationship would indicate the opposite of a bias because larger samples of arboreta show potential niches that are most similar to the realized niches, while smaller samples show potential niches much wider than realized niche widths. Potential niche width was positively yet weakly (R2 = 0.03) correlated with number of occurrences in arboreta. Niche contraction was uncorrelated with the number of occurrences in arboreta. Overall, the number of occurrences in arboreta did not systematically bias niche metrics. The occurrence records of trees in arboreta provide valuable information about whether mature individuals of a species can grow and survive in the conditions of the arboretum. Arboreta occurrences are valuable because they eliminate dispersal limitation and minimize competition. However, these records do not directly measure fundamental niches because no information was available on reproductive rates, failed cultivations, pest and disease control, soil properties, or the demographic data that is needed to quantify the population growth rate of the species (4, 5, 7). Analyses of population growth rates would constitute a stronger test of niche theory because they could be used to generate estimates of fitness optima (2), but the necessary experiments to generate this data cannot be conducted at continental scales with current resources. Our focus on occurrence data allows us to quantify both realized and potential thermal niches using the same ecological currency: growth and survival, and survival is the most influential fitness component for trees with stable age distributions (8). While aspects of the precipitation regime are of great interest, we focused on temperature exclusively because the arboreta could have initially supplemented water, which means that these estimates of thermal niches are best perceived as maximum temperatures in a possibly above-average precipitation regime (6). No arboretums occur below a mean annual temperature of 0 °C (Fig. S1), which could be a potential bias of our estimates of potential niches at the cold end of the gradient. However, it is unlikely that trees will survive at colder temperatures beyond the observed cold limits for physiological reasons. Alpine ecologists have demonstrated that ~ 6 °C average temperature of the growing season is the temperature limit at tree line (54). Moreover, a 6 °C average temperature of the growing season corresponds to a MAT of -11.4 °C (confidence interval range: -14.6, -4.4) (Fig. S7), and we observed the coldest realized niche minimum at -10 °C MAT, which closely agrees with the tree line temperature limit (Fig. 2A). Given that neither competition nor dispersal limitation can be invoked to explain tree lines, this lower limit likely represents the cold limit of both realized and potential niches of cold-tolerant species. Fig. S1. Geographic and climatic distributions of arboreta and realized occurrences in North America. Distributions of arboreta around the world in (A) Whittaker biome climate space and (B) geographical space. Distributions of occurrence data using BIEN and Little’s range maps in (C) Whittaker biome climate space and (D) geographical space (bio1 = mean annual temperature). R:P Ratio 15 10 5 0 Number of species 0 50 100 150 200 Number of occurrences in arboreta 0.4 0.5 0.6 0.7 0.8 0.9 1.0 B 20 A R^2 = 0.06 250 100 150 200 Number of occurrences in arboreta 250 50 100 150 200 Number of occurrences in arboreta 250 D 5 R^2 = 0.02 50 100 150 200 Number of occurrences in arboreta 250 0.4 0.2 0.0 −0.4 Niche contraction 20 15 10 Potential niche width 0.6 C 50 Fig. S2. Distribution of number of occurrences in botanical gardens for each species and their lack of systematic bias on the calculation of niche metrics for mean annual temperature. Thermal Niches of North American Tree Species Tree occurrences in BIEN and Little's maps (min to max) Tsuga mertensiana Picea sitchensis Alnus rubra Tsuga Tree occurrences in global arboreta (min to max) heterophylla Callitropsis nootkatensis Thuja plicata Abies amabilis Picea glauca Crataegus douglasii Betula papyrifera Amelanchier alnifolia Pinus contorta Picea mariana Taxus brevifolia Abies lasiocar pa Picea engelmannii Acer glabrum Amelanchier bar tramiana Populus balsamifera Juniperus scopulorum Cornus nuttallii Malus fusca Pseudotsuga menziesii Acer macrophyllum Pinus monticola Populus tremuloides Larix laricina Pinus aristata Pinus flexilis Abies balsamea Sorbus americana Picea pungens Abies grandis Arbutus menziesii Picea rubens Chamaecyparis lawsoniana Amelanchier stolonifera Prunus pensylvanica Quercus garryana Notholithocar pus densiflorus Umbellularia californica Acer spicatum Abies concolor Abies procera Pinus banksiana Prunus virginiana Amelanchier spicata Larix occidentalis Quercus agrifolia Juniperus occidentalis Torreya californica Pinus strobus Pinus attenuata Amelanchier utahensis Quercus gambelii Aesculus californica Acer pensylvanicum Betula populifolia Abies magnifica Betula alleghaniensis Pinus jeffreyi Amelanchier sanguinea Alnus rhombifolia Pinus ponderosa Thuja occidentalis Populus grandidentata Quercus kelloggii Quercus lobata Fraxinus nigra Quercus wislizeni Acer saccharum Amelanchier laevis Tsuga canadensis Amelanchier canadensis Pinus resinosa Acer rubrum Amelanchier arborea Crataegus macrosperma Ulmus americana Fagus grandifolia Cercocarpus ledifolius Crataegus flabellata Crataegus chrysocarpa Pinus coulteri Quercus rubra Fraxinus americana Aesculus flava Fraxinus pennsylvanica Ostrya virginiana Quercus chrysolepis Tilia amer icana Prunus serotina Acer negundo Crataegus coccinea Picea breweriana Calocedrus decurrens Crataegus punctata Betula lenta Pinus rigida Crataegus submollis Platanus racemosa Juniperus deppeana Acer grandidentatum Pinus lambertiana Juglans cinerea Quercus macrocarpa Robinia pseudoacacia Carpinus caroliniana Ulmus rubra Acer saccharinum Pinus monophylla Pinus edulis Quercus michauxii Quercus ellipsoidalis Quercus alba Quercus coccinea Crataegus crus−galli Carya ovata Crataegus intricata Malus coronaria Crataegus succulenta Oxydendrum arboreum Juniperus monosperma Carya cordiformis Crataegus pedicellata Nyssa sylvatica Platanus occidentalis Juniperus virginiana Liriodendron tulipifera Carya glabra Quercus bicolor Populus deltoides Pinus virginiana Pseudotsuga macrocar pa Sassafras albidum Quercus velutina Crataegus coccinioides Salix nigra Crataegus calpodendron Cornus florida Pinus echinata Quercus douglasii Prosopis glandulosa Crataegus mollis Juglans nigra Cercis canadensis Quercus palustris Celtis occidentalis Asimina triloba Ilex opaca Crataegus phaenopyrum Morus rubra Quercus muehlenbergii Quercus stellata Pinus sabiniana Quercus marilandica Malus angustifolia Gleditsia tr iacanthos Liquidambar styraciflua Betula nigra Malus ioensis Aesculus glabra Maclura pomifera Quercus falcata Quercus shumardii Persea borbonia Aesculus sylvatica Quercus phellos Quercus virginiana Ulmus alata Quercus nigra Gordonia lasianthus Aesculus pavia Quercus laurifolia Quercus pagoda Pinus taeda Taxodium distichum Nyssa aquatica Carya illinoinensis Taxodium ascendens Pinus elliottii Carya aquatica Celtis laevigata Quercus lyrata Crataegus marshallii Crataegus viridis Quercus texana Ulmus crassifolia Niche contraction Cooler Warmer Realized niche Potential niche 10 20 30 40 Maximum Temperature of Warmest Month (°C) Fig. S3. Empirical estimates of the potential and realized thermal niches of North American trees along a gradient of maximum temperature of the warmest month. Empirical estimates of realized and potential niches of 188 North American tree species along a gradient of maximum temperature of the warmest month. Realized niches (denoted by hash marks) are subsets of potential niches. Species are ordered by increasing realized niche minima. Niche minima and maxima are defined as the 0.01 and 0.99 quantiles of their distributions to remove effects of extreme outliers. All species have a potential niche that overlaps the central temperature (solid vertical line) of 25.5 ℃. The grey horizontal line denotes the range of temperatures sampled by BIEN and Little’s range maps, and the black horizonal line denotes the range of temperatures of the arboreta. The vertical line represents the mean value of the estimated maximum, x-intercept, and minimum from fitted regression models in Fig. 3 in the main text. Thermal Niches of North American Tree Species Tree occurrences in BIEN and Little's maps (min to max) Tree occurrences in global arboreta (min to max) Picea mariana Picea glauca Populus tremuloides Larix laricina Betula papyrifera Pinus banksiana Populus balsamifera Amelanchier alnifolia Abies balsamea Prunus pensylvanica Abies lasiocar pa Amelanchier bar tramiana Pinus contorta Amelanchier stolonifera Sorbus americana Prunus virginiana Thuja occidentalis Acer spicatum Amelanchier spicata Pinus aristata Pinus flexilis Amelanchier sanguinea Fraxinus nigra Picea engelmannii Pinus resinosa Picea pungens Ulmus americana Acer negundo Crataegus chrysocarpa Juniperus scopulorum Fraxinus pennsylvanica Quercus macrocarpa Pinus strobus Crataegus douglasii Populus grandidentata Tsuga heterophylla Crataegus succulenta Amelanchier utahensis Betula alleghaniensis Pseudotsuga menziesii Acer saccharum Quercus gambelii Thuja plicata Acer rubrum Abies concolor Tilia amer icana Acer glabrum Quercus rubra Ostrya virginiana Tsuga mertensiana Acer pensylvanicum Amelanchier arborea Pinus monticola Picea rubens Cercocarpus ledifolius Amelanchier laevis Quercus ellipsoidalis Taxus brevifolia Tsuga canadensis Fagus grandifolia Crataegus macrosperma Fraxinus americana Crataegus punctata Populus deltoides Larix occidentalis Alnus rubra Abies amabilis Crataegus submollis Crataegus flabellata Betula populifolia Celtis occidentalis Acer saccharinum Pinus ponderosa Juglans cinerea Acer grandidentatum Picea sitchensis Amelanchier canadensis Ulmus rubra Prunus serotina Abies grandis Carpinus caroliniana Pinus edulis Crataegus mollis Carya cordiformis Quercus bicolor Crataegus coccinioides Pinus jeffreyi Salix nigra Malus ioensis Callitropsis nootkatensis Juniperus occidentalis Pinus monophylla Juniperus virginiana Quercus alba Crataegus crus−galli Crataegus calpodendron Abies magnifica Juglans nigra Pinus rigida Carya ovata Crataegus phaenopyrum Betula lenta Morus rubra Quercus velutina Betula nigra Crataegus pedicellata Crataegus intricata Juniperus monosperma Robinia pseudoacacia Malus coronaria Gleditsia tr iacanthos Cornus nuttallii Quercus muehlenbergii Crataegus coccinea Alnus rhombifolia Aesculus glabra Abies procera Platanus occidentalis Quercus coccinea Quercus palustris Quercus kelloggii Sassafras albidum Calocedrus decurrens Picea breweriana Acer macrophyllum Carya glabra Pinus lambertiana Nyssa sylvatica Maclura pomifera Cornus florida Liriodendron tulipifera Asimina tr iloba Quercus chrysolepis Cercis canadensis Juniperus deppeana Pinus coulteri Quercus michauxii Torreya californica Pinus virginiana Quercus garryana Quercus marilandica Pinus attenuata Malus fusca Quercus shumardii Quercus stellata Aesculus flava Pseudotsuga macrocar pa Carya illinoinensis Arbutus menziesii Quercus wislizeni Notholithocarpus densiflorus Crataegus viridis Pinus echinata Oxydendrum arboreum Pinus sabiniana Chamaecyparis lawsoniana Ilex opaca Malus angustifolia Umbellularia californica Platanus racemosa Liquidambar styraciflua Celtis laevigata Ulmus alata Quercus lobata Quercus falcata Aesculus pavia Aesculus californica Quercus lyrata Quercus douglasii Quercus phellos Quercus agrifolia Prosopis glandulosa Nyssa aquatica Taxodium distichum Quercus pagoda Carya aquatica Quercus texana Aesculus sylvatica Pinus taeda Quercus nigra Crataegus marshallii Ulmus crassifolia Persea borbonia Quercus laurifolia Gordonia lasianthus Taxodium ascendens Quercus virginiana Pinus elliottii Niche contraction Cooler Warmer Realized niche Potential niche −30 −20 −10 0 10 20 Minimum Temperature of Coldest Month (°C) Fig. S4. Empirical estimates of the potential and realized thermal niches of North American trees along a gradient of minimum temperature of the coldest month. Empirical estimates of realized and potential niches of 188 North American tree species along a gradient of minimum temperature of the coldest month. Realized niches (denoted by hash marks) are subsets of potential niches. Species are ordered by increasing realized niche minima. Niche minima and maxima are defined as the 0.01 and 0.99 quantiles of their distributions to remove effects of extreme outliers. Most species have a potential niche that overlaps the central temperature (solid vertical line) of -3.2 ℃. The grey horizontal line denotes the range of temperatures sampled by BIEN and Little’s range maps, and the black horizonal line denotes the range of temperatures of the arboreta. The vertical line represents the mean value of the estimated maximum and x-intercept from the fitted regression models in Fig. 3 in the main text. 5 Mean radial tree growth by species by site (FORAST dataset) 3 2 1 Radial tree growth (mm) 4 R2 = 0.05 5 10 15 Mean annual temperature (°C) Fig. S5. Mean radial tree growth rate by species by site in the FORAST tree ring dataset from the northeastern United States. A model fit to all the data is an increasing function, and the second-order term in the quadratic polynomial is not significant (grey line). However, if the two sites with divergent growth rates at the highest mean annual temperatures are removed (one of these sites has extremely fast growth rates for all species and are potential outliers and the warmest site is removed out of an abundance of caution to avoid few points that are highly leveraged), then the quadratic polynomial is highly significant with an optimum temperature for growth at 11.9 ℃. Data reanalyzed from based on the FORAST data (55, 56). Fig. S6. Mean annual temperature at present and at the last glacial maximum (LGM). Geographic distribution of mean annual temperatures in North America at present (A) and at the LGM (C) and frequency distributions of mean annual temperatures at the two time periods (B, D). Top row represents the present day. Bottom row represents the LGM. Vertical lines denote medians. Climate data based on WorldClim 1.4 (57) and ice sheet data based on Dalton et al. (58). Fig. S7. Relationship between summer temperature (bio10) and mean annual temperature (bio1). In the present day, a 6 ℃ summer temperature equates to a -11.4 ℃ mean annual temperature (MAT) with a 90% confidence interval of (-14.6, -4.4). In the last glacial maximum (LGM) a 6 ℃ summer temperature equates to a -6.34 ℃ mean annual temperature (MAT) with a 90% confidence interval of (-13.1, -1.3). Data from WorldClim 1.4 (57). Table S1. Results of model comparisons for three sets of temperature variables (minimum, mean, maximum) and three sets of niche metrics. These results provide details about the test statistics shown in Fig. 2, S3, and S4. Models in bold were selected as the best model using AIC and likelihood ratio tests (LRT). Model R2 AIC LRT Linear 0.06 -220 NA Quadratic 0.45 -320 F=134, P <0.0001 1st Niche contraction Linear 0.65 Quadratic 0.71 -286 -318 NA F=38, P<0.0001 2nd 1st Potential niche width Linear 0.24 940 NA 2nd Quadratic 0.29 929 F=13, P=0.0003 1st Linear 0.03 -220 NA 2nd Quadratic 0.27 -273 F=62, P<0.0001 1st Niche contraction Linear 0.59 Quadratic 0.60 -275 -275 NA F=2.3, P=0.12 1st 2nd Potential niche width Linear 0.42 1045 NA 2nd Quadratic 0.45 1037 F=10.2, P=0.0016 1st Linear 0.36 -171 NA 2nd Quadratic 0.47 -203 F=36, P<0.0001 1st Niche contraction Linear 0.62 Quadratic 0.67 -194 -218 NA F=28, P<0.0001 2nd 1st Potential niche width Linear 0.10 886 NA 2nd Quadratic 0.20 866 F=24, P=0.0002 1st Temperature Metric variable Mean R:P ratio annual temperature Minimum temperature of coldest month Maximum temperature of warmest month R:P ratio R:P ratio Model rank 2nd Table S2. Comparison of mean annual temperature (MAT) model results using different random samples from the BIEN and Little’s range map data generated from different starting conditions for the random number generator. The three sets sampled from BIEN and Little’s range maps using 10 times the number of botanical garden occurrences. Given their high similarity, we report results based on the first sample in the main text. Sample Statistic Sample 1 (reported in paper) Sample 2 Sample 3 Mean of samples R:P ratio Maximum 9.96 9.93 9.88 9.92 R2 0.45 0.48 0.46 0.46 x-intercept 12.01 11.99 11.82 11.94 R2 0.71 0.70 0.70 0.70 Minimum 15.96 16.51 15.80 16.09 R2 0.29 0.24 0.31 0.28 Niche contraction Potential niche width Mean 12.65 References and Notes 1. B. J. McGill, B. J. Enquist, E. Weiher, M. Westoby, Rebuilding community ecology from functional traits. Trends Ecol. Evol. 21, 178–185 (2006). doi:10.1016/j.tree.2006.02.002 Medline 2. J. 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